1. Field
The present disclosure relates generally to methods for detecting hidden messages. More particularly, aspects of the present disclosure relate to systems and methods for steganalysis to detect hidden messages in digital files.
2. Description of the Related Art
Steganography is the art and science to carry messages in covert channels, aiming to enable secretive communication by embedding data into digital files without any attention to the existence of the hidden message. The potential of exploiting steganography for covert dissemination is great: for example, a recent espionage issue reveals that steganography has been employed by a governmental intelligent agency. For several purposes, it is a heightened need to realize effective countermeasures for steganography. Steganalysis generally employs techniques of signal processing, feature mining and pattern recognition and aims at detecting the existence of hidden messages.
In steganography, digital images may be easily manipulated to carry hidden messages. Examples of steganographic algorithms/systems include LSB embedding, LSB matching, spread spectrum steganography, Outguess, F5, model-based steganography, Steghide, BCH syndrome code based less detectable JPEG steganography, and highly undetectable steganography (HUGO).
Recent advances in steganography, such as adaptive steganography in DCT domain with optimized costs to achieve the minimal-distortion, have posed serious challenges to steganalyzers. Well-designed steganographic systems, such as Gibbs construction-based steganography, Syndrome-Trellis Codes based steganography, have posed additional challenges for steganalysis. In addition, Filler and Fridrich have proposed a practical framework of adaptive steganographic systems by optimizing the parameters of additive distortion functions and minimizing the distortion for ±1 embedding in the DCT domain, which has further advanced hiding data in wide-spread JPEG images.
Yet Another Steganographic Scheme (“YASS”) was designed to be a secure JPEG steganographic algorithm with randomized embedding. Some methods have been developed for steganalysis of YASS systems. The detection of the YASS steganograms produced by a large B-block parameter, however, has not been well explored.